code: def test_processing_of_initial_data_points(parameters):
      data_points_df = pandas.DataFrame(
          collections.OrderedDict(
              [
                  ("dropout", [0.5, 0.1, 0.3]),
                  ("lr", [1e-4, 1e-3, 1e-7]),
                  ("activation", ["relu", "tanh", "sigmoid"]),
                  ("num_hidden", [101, 202, 299]),
              ]
          )
      )
  
      data_points = GPyOpt._process_initial_data_points(
          data_points_df, parameters
      )
  
      assert data_points == [
          {
              "activation": "relu",
              "dropout": 0.5,
              "lr": 0.0001,
              "num_hidden": 101,
          },
          {
              "activation": "tanh",
              "dropout": 0.1,
              "lr": 0.001,
              "num_hidden": 202,
          },
          {
              "activation": "sigmoid",
              "dropout": 0.3,
              "lr": 1e-07,
              "num_hidden": 299,
          },
      ]
  
      with pytest.raises(ValueError):
          data_points_missing = GPyOpt._process_initial_data_points(
              data_points_df.drop("activation", axis=1), parameters
          )
  
imports: import sherpa
  import pandas
  import pytest
  import numpy
  import collections
  import GPyOpt
  from sherpa.algorithms.bayesian_optimization import GPyOpt
  from sherpa.algorithms import Repeat
label_desc: Use image node_id 6 for calling a global function with example usage: test_processing_of_initial_data_points(parameters) without return types